An individual's preferences can be complicated. The project investigates whether people's preferences do, in fact, conform to the CP-net (conditional preference network) formalism, how such preferences can be combined according to different voting methods, and how vulnerable those methods are to manipulation or "strategic voting." Finally, the very large corpus of preference data from the Netflix Challenge is used to build statistical models of the efficiency of manipulation algorithms and to compare the performance of different consensus methods.
Laboratory experiments will check whether people exhibit preferences that can be modeled by CP-nets. The project extends ideas from aggregation in Bayesian networks (models of conditional probabilities) to aggregation in CP-nets (models of conditional preferences).
The team investigates how statistical inference from noisy data relates to or interacts with strategic manipulability and bribery. The project extends behavioral social choice and computational social choice on voting systems, and the manipulation thereof, from preferences expressed as ratings, rankings, or subsets to preferences expressed as CP-nets.
The team investigates the performance of voting methods and the efficiency of manipulation schemes on real preference data from the Netflix challenge data set. These data, namely hundreds of thousands of (slightly perturbed) personal rankings of movies, were released several years ago for data-mining purposes. One can extract individual "elections" based on the rankings of a small set of movies, evaluate and compare various aggregation methods and empirically characterize voting scenarios that are especially susceptible or especially resilient to strategic manipulation.
Among the broader impacts of the research, beyond the integration and cross-fertilization of several distinct research areas spanning several scientific disciplines, are the development of more adequate individual and collective decision making tools, that will help individuals, groups, organizations, and society to improve decision making.
